CommuniTech Recruitment Group
Lead Data Engineer - Python/ AWS. Asset Management. £120,000 -£140,000+ Discretionary Bonus + Benefits. Hybrid 2 Days a week in Central London office.
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Lead Data Engineer - Python/ AWS. Asset Management. £120,000 -£140,000+ Discretionary Bonus + Benefits. Hybrid 2 Days a week in Central London office.
Lead Data Engineer – Python/AWS | Asset Management
£120,000–£140,000+ (Discretionary Bonus + Benefits) | Hybrid (2 Days in Central London)
A US$5bn+ global alternative asset manager operating across 7 offices (NYC, BVI, London, Switzerland, Dubai, Singapore, Hong Kong) seeks a Lead Data Engineer to help evolve their cloud-native data platform alongside two experienced engineers.
This is not a tick-box engineering role. You’ll collaborate closely with operations, research, and investment teams to solve real business problems, improve data reliability, and drive end-to-end solutions.
About the Role
The firm’s tech function is a lean, high-impact team of three engineers led by the COO. Every hire has significant ownership, direct influence on the platform, and close alignment with senior leadership and stakeholders.
You’ll work with existing production pipelines and build new capabilities, shifting priorities based on business needs. This role demands strong data engineering fundamentals, a production-first mindset, and the ability to cross-team collaboration when required.
Key Responsibilities
- Solve business problems—identify bottlenecks, inefficiencies, and data delays across ops, research, and investment teams.
- Improve the end-to-end data platform—ETL, transformation, storage, serving, observability, and reliability.
- Optimise data flow—reduce latency, eliminate stale data, and improve alerting to prevent silent failures.
- Design and maintain data architecture—break silos, streamline vendor-to-consumer workflows, and reduce unnecessary handoffs.
- Operate production pipelines—ingest and process financial data from major vendors.
- Build new integrations—develop vendor APIs, data products, and pipeline features.
- Manage AWS infrastructure—use Terraform for IaC, ensuring scalability and reliability.
- Integrate AI/ML capabilities—develop RAG pipelines and OCR-based document extraction to unlock unstructured data.
- Collaborate with the full engineering team—work on systems tied to their NextJS client-facing application.
- Prioritise work—align technical and non-technical stakeholders on priorities.
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Tools & Technologies
Primary: ✅ Python (ETL, API clients, data validation, CI/CD pipelines) ✅ SQL (analytical & transactional queries, transformations) ✅ AWS (cloud infrastructure, managed services) ✅ Terraform (Infrastructure-as-Code) ✅ MongoDB (document storage)
Observability & CI/CD: ✅ Monitoring tools (alerting, debugging) ✅ GitHub Actions (CI/CD pipelines)
Supporting (Helpful but not full-stack): 🔹 NextJS / TypeScript (exposure welcome) 🔹 Claude Code, Cursor, Codex (AI engineering tools in daily workflow) 🔹 Linear (project planning & task management)
Requirements
Must Have:
- Proven experience as a Data Engineer or similar role.
- Ability to identify business problems and deliver end-to-end data solutions, not just technical implementations.
- Strong Python & SQL skills.
- Hands-on AWS experience (including managed services).
- Infrastructure-as-Code (Terraform preferred).
- Production comfort—monitoring, incident response, debugging distributed systems.
- Stakeholder communication for non-technical teams.
- Experience integrating modern AI tools into daily workflows.
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Nice to Have:
✔ Financial services, asset management, or hedge fund experience. ✔ MongoDB experience. ✔ Familiarity with modern data tooling (e.g., data lakes, data meshes). ✔ Vendor API integrations knowledge. ✔ Experience with LLM-based document processing (RAG, OCR). ✔ Exposure to NextJS / TypeScript (preferred but not mandatory).
Who You Are
You’ll thrive here if you: ✔ Proactively solve problems—don’t wait for requirements; drive solutions. ✔ Own systems end-to-end—comfortable with high autonomy in a small team. ✔ Context-switch efficiently—balance new features and production stability. ✔ Prefer pragmatic over over-engineered—simple, scalable solutions matter. ✔ Wear multiple hats—interact with stakeholders, debug systems, and implement changes. ✔ Communicate clearly—bridging technical and non-technical teams naturally.
Next Steps
Apply now—send your CV for immediate consideration.
Hybrid: 2 days in London office (Central London).
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